Article: Modelling COVID-19 incidence in the African sub-region using smooth transition autoregressive model.
Modeling earth systems and environment
2021 Volume 8, Issue 1, Page(s) 961–966
Abstract: ... autoregressive (STAR) model for improved forecasting of COVID-19 incidence in the Africa sub-region were ... Prediction of COVID-19 incidence and transmissibility rates are essential to inform disease control ... investigated. Data used in the study were daily confirmed new cases of COVID-19 from February 25 to August 31 ...
| Abstract | Prediction of COVID-19 incidence and transmissibility rates are essential to inform disease control policy and allocation of limited resources (especially to hotspots), and also to prepare towards healthcare facilities demand. This study demonstrates the capabilities of nonlinear smooth transition autoregressive (STAR) model for improved forecasting of COVID-19 incidence in the Africa sub-region were investigated. Data used in the study were daily confirmed new cases of COVID-19 from February 25 to August 31, 2020. The results from the study showed the nonlinear STAR-type model with logistic transition function aptly captured the nonlinear dynamics in the data and provided a better fit for the data than the linear model. The nonlinear STAR-type model further outperformed the linear autoregressive model for predicting both in-sample and out-of-sample incidence. |
|---|---|
| Language | English |
| Publishing date | 2021-02-26 |
| Publishing country | Netherlands |
| Document type | Journal Article |
| ZDB-ID | 2821317-8 |
| ISSN | 2363-6211 ; 2363-6203 |
| ISSN (online) | 2363-6211 |
| ISSN | 2363-6203 |
| DOI | 10.1007/s40808-021-01136-1 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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